Data Analysis

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The Best Python Books for Data Analysts

What role do books play in acquiring data analysis skills? Discover how you can benefit from the best Python books for data analysts – and how to use them as a supplementary learning material. Data is a highly valuable asset. In fact, we might even argue that it’s the most valuable asset in the 21st century. The success and performance of products depends on the quality of input data. However, data in its raw form does not give us its full potential.

Jakub Romanowski

Just How Valuable Is Python for Business?

If you're wondering how Python can reshape your business, this article is for you. We’ll look at the practical applications of using Python for Business and discuss why implementing Python tools might be a smart move for your organization. Python is definitely having a moment – or maybe a decade! Implementing Python for business uses – especially in data analysis – is transforming the way companies handle data, analytics, and automation.

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Why Should I Learn Python for Data Analysis?

Do you actually need Python to become a data analyst? Discover why you should learn Python and how you can benefit from it as a data analyst. Data is ubiquitous. From retail stores to digital marketing agencies, from sports teams to production sites, numerous industries use data in their operations to improve productivity, efficiency, productivity, or any other metric that’s important for them. They unlock the power of data, which has the potential to offer valuable insights, which are difficult for the human eye to catch.

Xavier Rigoulet

Learn Python for Data Analysis

This guide is your first step towards mastering Python for data analysis and turning your data into actionable insights. Information is king, but what good is a mountain of data if you can't unlock its secrets? Have you ever wished you could transform raw numbers into actionable insights that drive better decisions? If you answered yes, then Python for data analysis is the key you've been searching for. This powerful skill empowers you to extract meaning from data, transforming you from a passive observer into an informed decision-maker that helps businesses reach the next level.

Luke Hande

Python Data Analysis Example: A Step-by-Step Guide for Beginners

Doing real data analysis exercises is a great way to learn. But data analysis is a broad topic, and knowing how to proceed can be half the battle. In this step-by-step guide, we’ll show you a Python data analysis example and demonstrate how to analyze a dataset. A great way to get practical experience in Python and accelerate your learning is by doing data analysis challenges. This will expose you to several key Python concepts, such as working with different file types, manipulating various data types (e.

Alexandre Bruffa

15 Top Python Interview Questions for Data Analysts

Coding – particularly in Python – is an important skill for data analysis roles. Check out these 15 Python interview questions specifically for data analysts and get a head start on your next job interview! Python has become one of the world’s favorite programming languages. Its robust ecosystem of data-handling libraries has made it an excellent (and in-demand) tool for data analysts. Whether you're a seasoned data enthusiast or just embarking on your journey into the field of data analysis, preparing for a data analyst interview is essential.

Luke Hande

A Practical Guide to Python for Data Science

Working on real data science projects is a rewarding experience. But how do you get to the point where you can make a real contribution? What skills and experience do you need? What challenges might occur along the way? In this article, we’ll address all these questions. Data has become ubiquitous in our modern world. It’s generated from many sources, including social media, IoT devices, business transactions, finance, government and public records, academic research, communication systems, and even satellites and remote sensing technology.

Xavier Rigoulet

Python Data Analysis Example: Ames Housing Dataset

Are you curious about analyzing data with Python? This article walks you through a step-by-step Python data analysis example. Have you ever wondered how companies make informed decisions based on vast amounts of data? Have you ever found yourself staring at a dataset, wondering where to start your data analysis? This article will guide you through the process of conducting data analyses in Python and transforming data into actionable knowledge.

Luke Hande

7 Datasets to Practice Data Analysis in Python

Data analysis is a skill that is becoming more essential in today's data-driven world. One effective way to practice with Python is to take on your own data analysis projects. In this article, we’ll show you 7 datasets you can start working on. Python is a great tool for data analysis – in fact,  it has become very popular, as we discuss in Python’s Role in Big Data and Analytics.

Xavier Rigoulet

Python Data Cleaning: A How-to Guide for Beginners

Have you ever wondered why your data analysis sometimes yields unexpected results or errors? Do you know how to ensure the data for your project is accurate and reliable? Are you curious about the tools and techniques data professionals use to clean messy datasets? Have you ever struggled with data containing misspelled words, mixed-case text, or missing values? Would you like to discover how Python, a versatile programming language, helps you automate the process of data cleaning?

Luke Hande

Python Exploratory Data Analysis Cheat Sheet

Get a quick overview of exploratory data analysis, a process used to summarize your dataset and get some quick insights. We’ll give you the tools and techniques you need in this cheat sheet. Exploratory data analysis (EDA) is a term used to describe the process of starting to analyze your data in the early stages. Its primary purpose is to understand the properties of the data, with the aim of using these insights to refine the analysis to derive the best insights possible from the data you have.

Xavier Rigoulet

Python’s Role in Big Data and Analytics

Python is crucial for Big Data and data analysis. Want to know why? In this article, we’ll explain how learning Python can help you to get ahead and boost your career. Python is a popular programming language that is widely embraced by beginners and experienced developers alike. It was created over 30 years ago, but it’s stillworth learning in 2023 for several reasons – not least of which is that Python is essential to Big Data and data analytics.

András Novoszáth

The Top 5 Python Libraries for Data Visualization

Which Python library should you pick for data visualization? Read on to see our assessment! Data visualization is an increasingly valuable skill, one that’s sought after in many organizations. It helps you to find insight into data and to communicate your findings to less technical audiences. You can benefit from it in your career and use it to pivot toward a data-focused role. There are many paths to learning and practicing data visualization.

Kateryna Koidan

Python or R: Which to Learn as a New Data Analyst?

Thinking about becoming a data analyst? It’s a very promising career path, but data analysts are often required to master at least one programming language. Let’s explore whether this should be Python or R. If you scroll through a couple of data analyst job descriptions, you’ll notice that most of them have a requirement for at least one programming language – Python, R, or SQL. SQL is somewhat unique as the key language for communicating with relational databases.

Usman Malik

Excel Alternative: What to Learn as a Data Analyst

Excel spreadsheets are quickly becoming obsolete thanks to the emergence of the latest data analytics tools and languages such as Python, Java, R, and Microsoft HDInsight. However, a large number of companies still use digital spreadsheets, creating a lot of problems for modern business data analysts. Analyzing data through excel is a poor choice because of reasons like errors in data validation, a poor shared workbook feature, no multi-user editing, inaccurate data, and safety concerns, making it necessary for you to switch to better and advanced alternatives.